• PAN-OS’s latest industry-leading upgrade software uses cloud computing to detect highly evasive threats quickly and effectively.
  • PAN-OS 10.2 Nebula can successfully collect, analyze, and interpret potential zero-day threats in real time.

Palo Alto Networks, a 10-time leader in network firewalls, announced the release of Nebula, the latest upgrade of its industry-leading PAN-OS software. The software aims to help find the evasive, zero-day attacks that can cripple organizations and stop them in their tracks.

PAN-OS 10.2 Nebula can successfully collect, analyze, and interpret potential zero-day threats in real time with the help of inline deep learning – network security first. This leads to six times faster prevention and about 48% more evasive threats discovered, outstripping anything previously possible.

Nebula also brings AIOps – Palo Alto Networks tenth security service and the new Advanced Threat Prevention service. This also includes improvements in Advanced URL (Uniform Resource Locator) Filtering, DNS (Domain Name System) Security, IoT (Internet of Things) Security, and other associated security services.

“In the past, nation-state-led cyberattacks were considered the rarest and most advanced. But today, attackers of all kinds have an advanced arsenal at their fingertips; every organization must now assume they will be the target of a nation-state-level attack,” said Lee Klarich, Chief Product Officer, Palo Alto Networks. “Modern network security requires a fundamentally new approach. Today, Palo Alto Networks has brought that new approach to our ML-Powered Next-Generation Firewalls by harnessing the processing power of the cloud to enable deep learning inline. We believe that is how all network security will be done in the future.”

Security services that are being enhanced and added comprise:

  • Advanced Threat Prevention: This new best-in-class Intrusion Prevention System (IPS) presents security analysis from ‘offline’ to ‘inline’ through cloud computing for Artificial Intelligence (AI) and deep learning techniques by keeping performance intact. Advanced Threat Prevention identifies many unknown and targeted command and control (C2) attacks along with evasive attacks from tools such as Cobalt Strike.
  • AIOps: With the help of Machine Learning (ML), the new AIOps can predict up to 51% of disruptions to Next Generation Firewall (NGFW) before impacting the firewalls. Additionally, with telemetry from over 6,000 deployments, AIOps constantly advise on best practices to improve overall security posture.
  • DNS Security: Extends protection for the latest DNS-based attack techniques, including strategically aged domains, making it the most comprehensive DNS security solution. This solution is available with 40% more DNS-based threat coverage than other leading vendors.
  • Advanced URL Filtering: This prevents new, highly evasive phishing attacks, ransomware, and other web-based attacks. It is performed using deep learning-powered analysis of web traffic, which now includes live web content in real time and inline.
  • IoT Security 2.0: This service simplifies IoT device visibility and automates policy creation across seen and unseen devices with the help of ML.

“Security approaches are too often reliant on an initial victim being exploited. Yet, with attackers as agile and efficient as they are today, organizations require real-time prevention to protect their environments,” said John Grady, Senior Analyst at the Enterprise Strategy Group (ESG). “Palo Alto Networks recognizes these issues and is expanding its machine learning capabilities by placing Deep Learning detection inline to prevent attacks before they ever impact victim one.”

“Palo Alto Networks’ industry-leading machine learning-based platform applies techniques that help customers handle sophisticated threats and meet end-to-end demands across network, endpoint, and cloud security. The company enables enterprises to go beyond standard threat protection by building a strong security posture and resilience,” said Rajarshi Dhar, Industry Analyst, Frost and amp; Sullivan.